Irritability in bipolar disorder and unipolar disorder measured daily using smartphone-based data: An exploratory post hoc study.

OBJECTIVE: To investigate (i) the proportions of time with irritability and (ii) the association between irritability and affective symptoms and functioning, stress, and quality of life in patients with bipolar disorder (BD) and unipolar depressive disorder (UD). METHODS: A total of 316 patients with BD and 58 patients with UD provided self-reported once-a-day data on irritability and other affective symptoms using smartphones for a total of 64,129 days with observations. Questionnaires on perceived stress and quality of life and clinical evaluations of functioning were collected multiple times during the study. RESULTS: During a depressive state, patients with UD spent a significantly higher proportion of time with presence of irritability (83.10%) as compared with patients with BD (70.27%) (p = 0.045). Irritability was associated with lower mood, activity level and sleep duration and with increased stress and anxiety level, in both patient groups (p-values<0.008). Increased irritability was associated with impaired functioning and increased perceived stress (p-values<0.024). In addition, in patients with UD, increased irritability was associated with decreased quality of life (p = 0.002). The results were not altered when adjusting for psychopharmacological treatments. CONCLUSIONS: Irritability is an important part of the symptomatology in affective disorders. Clinicians could have focus on symptoms of irritability in both patients with BD and UD during their course of illness. Future studies investigating treatment effects on irritability would be interesting.

Discriminating between patients with unipolar disorder, bipolar disorder, and healthy control individuals based on voice features collected from naturalistic smartphone calls.

BACKGROUND: It is of crucial importance to be able to discriminate unipolar disorder (UD) from bipolar disorder (BD), as treatments, as well as course of illness, differ between the two disorders. AIMS: To investigate whether voice features from naturalistic phone calls could discriminate between (1) UD, BD, and healthy control individuals (HC); (2) different states within UD. METHODS: Voice features were collected daily during naturalistic phone calls for up to 972 days. A total of 48 patients with UD, 121 patients with BD, and 38 HC were included. A total of 115,483 voice data entries were collected (UD [n = 16,454], BD [n = 78,733], and HC [n = 20,296]). Patients evaluated symptoms daily using a smartphone-based system, making it possible to define illness states within UD and BD. Data were analyzed using random forest algorithms. RESULTS: Compared with BD, UD was classified with a specificity of 0.84 (SD: 0.07)/AUC of 0.58 (SD: 0.07) and compared with HC with a sensitivity of 0.74 (SD: 0.10)/AUC = 0.74 (SD: 0.06). Compared with BD during euthymia, UD during euthymia was classified with a specificity of 0.79 (SD: 0.05)/AUC = 0.43 (SD: 0.16). Compared with BD during depression, UD during depression was classified with a specificity of 0.81 (SD: 0.09)/AUC = 0.48 (SD: 0.12). Within UD, compared with euthymia, depression was classified with a specificity of 0.70 (SD 0.31)/AUC = 0.65 (SD: 0.11). In all models, the user-dependent models outperformed the user-independent models. CONCLUSIONS: The results from the present study are promising, but as reflected by the low AUCs, does not support that voice features collected during naturalistic phone calls at the current state of art can be implemented in clinical practice as a supplementary and assisting tool. Further studies are needed.

Right unilateral versus bilateral formula-based electroconvulsive therapy in the treatment of major depression in elderly patients: a randomised, open label, pilot controlled trial.

BACKGROUND: Electroconvulsive therapy (ECT) remains the most effective treatment of depression in the elderly population; however, it is still unclear which type of ECT is most beneficial in this population. The aims of this study were: (i) to assess the feasibility of a randomised controlled trial in elderly depressed patients treated with right unilateral (RUL) or fronto-temporal bilateral (BT) formula-based ECT; (ii) to compare formula-based RUL and BT ECT in terms of efficacy, safety and tolerability in this population. METHODS: The study lasted 3 years and managed to randomise 29 patients over 65 years old to receive either BT (n = 14) or RUL (n = 15) ECT. Brief pulse width (0.5 ms) and age-based dosing method were applied. The clinical efficacy was assessed using Hamilton Depression Rating Scale, somatic state was monitored throughout the ECT course. In neuropsychological examination general cognitive performance, executive functions, verbal fluency, memory, autobiographical memory were evaluated. RESULTS: The recruitment was poor due to small number of patients able to give informed consent. ECT proved to be a highly effective and safe method of treatment among elders. Formula-based RUL ECT did not differ from BT in antidepressant efficacy and had cognitive advantages - the indices of general cognitive performance, verbal fluency and memory were significantly better than before the treatment in the RUL group. Decline in retrieval consistency of autobiographical memory was more pronounced in the BT group, although it was observed across both groups. CONCLUSIONS: Formula-based RUL ECT might not differ from BT in antidepressant efficacy and has an advantage in terms of tolerability.

Differentiating unipolar and bipolar depression: Contribution of the Rorschach test (Comprehensive System).

OBJECTIVE: The aim of this study was to contribute to differential diagnoses of unipolar and bipolar depression using cognitive variables of the Rorschach test (Comprehensive System). METHOD: One hundred forty one depressed inpatients (71 bipolar, 70 unipolar; mean age = 46, SD = 15.8; 64% women) previously evaluated and comparable regarding clinical characteristics of their illness (including current mood symptoms) were blindly tested using the Rorschach test (C.S.). RESULTS: The cognitive profile of bipolar depressed patients was more impaired than the cognitive profile of unipolar depressed patients. Combining four cognitive specificities (tolerance to ambiguity, discrimination failure, difficulties in controlling ideational impulses, and impulsive or negligent processing) in a logistic regression model allows the identification of bipolarity with acceptable accuracy. CONCLUSIONS: Some aspects of cognitive functioning, as assessed with the Rorschach test (CS), appear to be useful to capture some important cognitive specificities of bipolar depression and could contribute to differential diagnoses of mood disorders.

Mixed states in bipolar and major depressive disorders: systematic review and quality appraisal of guidelines.

OBJECTIVE: This systematic review provided a critical synthesis and a comprehensive overview of guidelines on the treatment of mixed states. METHOD: The MEDLINE/PubMed and EMBASE databases were systematically searched from inception to March 21st, 2018. International guidelines covering the treatment of mixed episodes, manic/hypomanic, or depressive episodes with mixed features were considered for inclusion. A methodological quality assessment was conducted with the Appraisal of Guidelines for Research and Evaluation-AGREE II. RESULTS: The final selection yielded six articles. Despite their heterogeneity, all guidelines agreed in interrupting an antidepressant monotherapy or adding mood-stabilizing medications. Olanzapine seemed to have the best evidence for acute mixed hypo/manic/depressive states and maintenance treatment. Aripiprazole and paliperidone were possible alternatives for acute hypo/manic mixed states. Lurasidone and ziprasidone were useful in acute mixed depression. Valproate was recommended for the prevention of new mixed episodes while lithium and quetiapine in preventing affective episodes of all polarities. Clozapine and electroconvulsive therapy were effective in refractory mixed episodes. The AGREE II overall assessment rate ranged between 42% and 92%, indicating different quality level of included guidelines. CONCLUSION: The unmet needs for the mixed symptoms treatment were associated with diagnostic issues and limitations of previous research, particularly for maintenance treatment.

Vascular endothelial growth factor plasma levels in depression and following electroconvulsive therapy.

Both animal and human studies have implicated the neurotrophic and angiogenic mediator vascular endothelial growth factor (VEGF) in depression, with meta-analyses, indicating that protein levels are raised in patients with depression. In line with this, we have previously shown that VEGFA mRNA levels are higher in whole blood from patients with depression compared to controls, in particular in patients with psychotic unipolar depression, and that treatment with electroconvulsive therapy (ECT) alters VEGFA mRNA levels. The aim of the present study was, therefore, to extend this previous work by assessing plasma VEGF protein levels in patients with depression compared to healthy controls, and in patients following treatment with ECT. We found that there was no difference between controls and patients with depression with regard to plasma VEGF (p = 0.59), and that VEGF levels were unaltered by ECT (p = 0.09) after correction for potential covariates. We found no correlation between VEGF protein and mRNA levels. Within the subgroup of patients receiving treatment with bitemporal ECT (n = 34), we identified a moderate negative correlation (ρ = - 0.54, p = 0.001) between the change in VEGF and the change in depression severity following treatment; however, no other association between VEGF and mood, responder/remitter status, polarity of depression, or presence of psychosis were found. Overall, our results indicate that the measurement of VEGF protein is not a useful marker for depression or response to treatment, and suggest that the measurement of VEGFA mRNA may prove more useful.

Early maladaptive schemas in patients with bipolar and unipolar disorder.

OBJECTIVE: The aim of our study is to determine the difference between the bipolar disorder, unipolar disorder and control groups in terms of maladaptive schemes and childhood trauma. METHODS: Two groups of patients under monitoring with a diagnosis of bipolar or unipolar disorder and one group of healthy controls were enrolled in this study. Each group consisted of 60 subjects. The Young Mania Rating Scale and Beck Depression Inventory were used to confirm that patients were in remission. The Childhood Trauma Questionnaire and Young Schema Questionnaire-Short Form 3 were used to identify childhood traumas and early maladaptive schemas. RESULTS: In bipolar disorder, a positive, low power correlation was observed between the vulnerability to threats schema and emotional, physical and sexual abuse. In the unipolar disorder group, there was a positive, low power correlation between the emotional inhibition, failure, approval seeking, dependence, abandonment and defectiveness schemas and social isolation, and a positive, moderate correlation between social isolation and emotional abuse. CONCLUSIONS: Individuals with bipolar disorder suffered greater childhood trauma compared to subjects with unipolar disorder and healthy individuals. Greater maladaptive schema activation were present in individuals with bipolar disorder compared to those with unipolar disorder and healthy individuals.

Sleep-wake cycle phenotypes in young people with familial and non-familial mood disorders.

OBJECTIVES: Converging evidence identifies that the offspring of parents with bipolar disorder (BD), individuals at clinical high risk of BD, and young people with recent onset BD may differ from other clinical cases or healthy controls in terms of sleep-wake profiles. However, it is possible that these differences may reflect current mental state, subtype of mood disorder, or familial traits. This study aimed to determine objective and subjective sleep-wake profiles in individuals aged 15-25 years with a current major depressive episode, in relation to familial traits. METHODS: Frequency matching was employed to ensure that each individual with a confirmed family history of BD (FH+) could be compared to four controls who did not have a familial mood disorder (FH-). Pre-selected objective actigraphy and subjective Pittsburgh Sleep Quality Index (PSQI) ratings were compared using one-way analysis of variance (ANOVA) and applying the Benjamini-Hochberg (BH) correction for false discoveries. RESULTS: The sample comprised 60 individuals with a mean age of 19 years. The FH+ (n=12) and FH- groups (n=48) differed on three key sleep parameters: mean sleep duration on week nights (P=.049), variability in waking after sleep onset (P=.038), and daily disturbances (PSQI dimension of sleep disturbance and daytime dysfunction; P=.01). CONCLUSIONS: The sleep profiles we identified in this study, especially the daily disturbances phenotype, provide support for research into endophenotypes for BD. Also, the findings may offer the opportunity for more tailored, personalized interventions that target specific components of the sleep-wake cycle in individuals with a family history of BD.

Test-retest reliability of schizoaffective disorder compared with schizophrenia, bipolar disorder, and unipolar depression--a systematic review and meta-analysis.

OBJECTIVES: Schizoaffective disorder is a frequent diagnosis, and its reliability is subject to ongoing discussion. We compared the diagnostic reliability of schizoaffective disorder with its main differential diagnoses. METHODS: We systematically searched Medline, Embase, and PsycInfo for all studies on the test-retest reliability of the diagnosis of schizoaffective disorder as compared with schizophrenia, bipolar disorder, and unipolar depression. We used meta-analytic methods to describe and compare Cohen's kappa as well as positive and negative agreement. In addition, multiple pre-specified and post hoc subgroup and sensitivity analyses were carried out. RESULTS: Out of 4,415 studies screened, 49 studies were included. Test-retest reliability of schizoaffective disorder was consistently lower than that of schizophrenia (in 39 out of 42 studies), bipolar disorder (27/33), and unipolar depression (29/35). The mean difference in kappa between schizoaffective disorder and the other diagnoses was approximately 0.2, and mean Cohen's kappa for schizoaffective disorder was 0.50 (95% confidence interval: 0.40-0.59). While findings were unequivocal and homogeneous for schizoaffective disorder's diagnostic reliability relative to its three main differential diagnoses (dichotomous: smaller versus larger), heterogeneity was substantial for continuous measures, even after subgroup and sensitivity analyses. CONCLUSIONS: In clinical practice and research, schizoaffective disorder's comparatively low diagnostic reliability should lead to increased efforts to correctly diagnose the disorder.

Electronic monitoring of psychomotor activity as a supplementary objective measure of depression severity.

BACKGROUND: Rating scales used to assess the severity of depression e.g. the Hamilton Depression Rating Scale 17-item (HDRS-17) partly rely on the patient's subjective experience and reporting. Such subjective measures tend to have low reliability and adding objective measures to complement the assessment of depression severity would be a major step forward. AIMS: To investigate correlations between electronic monitoring of psychomotor activity and severity of depression according to HDRS-17. METHODS: A total of 36 patients with unipolar disorder (n = 18) or bipolar disorder (n = 18) and 31 healthy control persons aged 18-60 years were included. Psychomotor activity was measured using a combined heart rate and movement sensor device (Actiheart) for 3 consecutive days, 24 h a day. RESULTS: We found that sleeping heart rate (beats/min) correlated with HDRS-17 in both patients with unipolar disorder and bipolar disorder (unadjusted model: B = 0.46, 95% CI 0.037-0.89, P = 0.034). In contrast, correlations between activity energy expenditure (kJ/kg/day), cardio-respiratory fitness (mlO2/min/kg) and HDRS-17 were non-significant. CONCLUSIONS: These results suggest that measuring sleeping heart rate in non-experimental daily life could be an objective supplementary method to measure the severity of depression and perhaps indicate presence of insomnia.

Response inhibition related neural oscillatory patterns show reliable early identification of bipolar from unipolar depression in a Go/No-Go task.

BACKGROUND: Response inhibition is a key neurocognitive factor contributing to impulsivity in mood disorders. Here, we explored the common and differential alterations of neural circuits associated with response inhibition in bipolar disorder (BD) and unipolar disorder (UD) and whether the oscillatory signatures can be used as early biomarkers in BD. METHODS: 39 patients with BD, 36 patients with UD, 29 patients initially diagnosed with UD who later underwent diagnostic conversion to BD, and 36 healthy controls performed a Go/No-Go task during MEG scanning. We carried out time-frequency and connectivity analysis on MEG data. Further, we performed machine learning using oscillatory features as input to identify bipolar from unipolar depression at the early clinical stage. RESULTS: Compared to healthy controls, patients had reduced rIFG-to-pre-SMA connectivity and delayed activity of rIFG. Among patients, lower beta power and higher peak frequency were observed in BD patients than in UD patients. These changes enabled accurate classification between BD and UD with an accuracy of approximately 80 %. CONCLUSIONS: The inefficiency of the prefrontal control network is a shared mechanism in mood disorders, while the abnormal activity of rIFG is more specific to BD. Neuronal responses during response inhibition could serve as a diagnostic biomarker for BD in early stage.

Using digital phenotyping to classify bipolar disorder and unipolar disorder - exploratory findings using machine learning models.

The aims were to investigate 1) differences in smartphone-based data on phone usage between bipolar disorder (BD) and unipolar disorder (UD) and 2) by using machine learning models, the sensitivity, specificity, and AUC of the combined smartphone data in classifying BD and UD. Daily smartphone-based self-assessments of mood and same-time passively collected smartphone data on smartphone usage was available for six months. A total of 64 patients with BD and 74 patients with UD were included. Patients with BD during euthymic states compared with UD in euthymic states had a lower number of incoming phone calls/ day (B: -0.70, 95%CI: -1.37; -0.70, p=0.040). Patients with BD during depressive states had a lower number of incoming and outgoing phone calls/ day as compared with patients with UD in depressive states. In classification by using machine learning models, 1) overall (regardless of the affective state), patients with BD were classified with an AUC of 0.84, which reduced to 0.48 when using a leave-one-patient-out crossvalidation (LOOCV) approach; similarly 2) during a depressive state, patients with BD were classified with an AUC of 0.86, which reduced to 0.42 with LOOCV; 3) during a euthymic state, patients with BD were classified with an AUC of 0.87, which reduced to 0.46 with LOOCV. While digital phenotyping shows promise in differentiating between patients with BD and UD, it highlights the challenge of generalizing to unseen individuals. It should serve as an complement to comprehensive clinical evaluation by clinicians.

Gamma band VMPFC-PreCG.L connection variation after the onset of negative emotional stimuli can predict mania in depressive patients.

OBJECTIVE: Because of the similar clinical symptoms, it is difficult to distinguish unipolar disorder (UD) from bipolar disorder (BD) in the depressive episode using the available clinical features, especially for those who meet the diagnostic criteria of UD, however, experience the manic episode during the follow-up (tBD). METHODS: Magnetoencephalography recordings during a sad expression recognition task were obtained from 81 patients (27 BD, 24 tBD, 30 UD) and 26 healthy controls (HCs). Source analysis was applied to localize 64 regions of interest in the low gamma band (30-50 Hz). Regional functional connections (FCs) were constructed respectively within three time periods (early: 0-200 ms, middle: 200-400 ms, and post: 400-600 ms). The network-based statistic method was used to explore the abnormal connection patterns in tBD compared to UD and HC. BD was applied to explore whether such abnormality is still significant between every two groups of BD, tBD, UD, and HC. RESULTS: The VMPFC-PreCG.L connection was found to be a significantly different connection between tBD and UD in the early time period and between tBD and BD in the middle time period. Furthermore, the middle/early time period ratio of FC value of VMPFC-PreCG.L connection was negatively correlated with the bipolarity index in tBD. CONCLUSIONS: The VMPFC-PreCG.L connection in different time periods after the onset of sad facial stimuli may be a potential biomarker to distinguish the different states of BD. The FC ratio of VMPFC-PreCG.L connection may predict whether patients with depressive episodes subsequently develop mania.

Shared and specific neurobiology in bipolar disorder and unipolar disorder: Evidence based on the connectome gradient and a transcriptome-connectome association study.

BACKGROUND: Distinguishing bipolar disorder (BD) and unipolar disorder (UD) remains challenging. To identify the common and diagnosis-specific neuropathological alterations and their potential molecular mechanisms in patients with UD and BD (with a current depressive episode). METHODS: Resting-state functional magnetic resonance imaging was obtained from 279 participants (95 BD patients, 107 UD patients and 77 health controls). Connectome gradients analysis was performed to explore the shared and diagnosis-specific gradient alterations in BD and UD. The Allen Human Brain Atlas data was used to explore the potential gene mechanisms of the gradient alterations. RESULTS: BD and UD had shared hierarchical disorganisation, including downgrading and contraction from the unimodal sensory networks (vision and sensorimotor) to the transmodal cognitive networks (limbic, frontoparietal, dorsal attention, and default) (all P < 0.05, FDR corrected) in gradient 1 and gradient 2. The BD patients had specific connectome gradient dysfunction in the subcortical network. Moreover, the hierarchical disorganisation was closely correlated with profiles of gene expression specific to the neuroglial cells in the prefrontal cortex in BD and UD, while the most correlated gene ontology biological processes and function were concentrated in synaptic signalling, calcium ion binding, and transmembrane transporter activity. CONCLUSION: These findings reveal the shared and diagnosis-specific neurobiological mechanism underlying BD and UD patients, which advances our understanding of the neuromechanisms of these disorders.

Distinct Predictors of Clinical Response after Repetitive Transcranial Magnetic Stimulation between Bipolar and Unipolar Disorders.

Background: Repetitive transcranial magnetic stimulation (rTMS) has been shown to be therapeutically effective for patients suffering from drug-resistant depression. The distinction between bipolar and unipolar disorders would be of great interests to better adapt their respective treatments. Methods: We aimed to identify the factors predicting clinical improvement at one month (M1) after the start of rTMS treatment for each diagnosis, which was preceded by a comparison of the patients' clinical conditions. We used the data collected and the method employed in a previous publication on 291 patients. Results: Although the bipolar group had fewer responders, these patients seemed to better maintain their post-rTMS improvement on anxiety and perception of the severity of their illness than those in the unipolar group. For the bipolar group, young age coupled with low number of medications and high fatigue was shown to be the best combination for predicting improvement at M1. The duration of current depressive episode, which was previously demonstrated for whole group, combined with being attached was shown to favor clinical improvement among the patients in unipolar group. Conclusion: We were able to define a combination of specific factors related to each diagnosis for predicting the patients' clinical response. This could be extremely useful to predict the efficacy of rTMS during routine clinical practice in neuromodulation services.

Differences in mobility patterns according to machine learning models in patients with bipolar disorder and patients with unipolar disorder.

BACKGROUND: It is essential to differentiate bipolar disorder (BD) from unipolar disorder (UD) as the course of illness and treatment guidelines differ between the two disorders. Measurements of activity and mobility could assist in this discrimination. AIMS: 1) To investigate differences in smartphone-based location data between BD and UD, and 2) to investigate the sensitivity, specificity, and AUC of combined location data in classifying BD and UD. METHODS: Patients with BD and UD completed smartphone-based self-assessments of mood for six months, along with same-time passively collected smartphone data on location reflecting mobility patterns, routine and location entropy (chaos). A total of 65 patients with BD and 75 patients with UD were included. RESULTS: A total of 2594 (patients with BD) and 2088 (patients with UD) observations of smartphone-based location data were available. During a depressive state, compared with patients with UD, patients with BD had statistically significantly lower mobility (e.g., total duration of moves per day (eB 0.74, 95% CI 0.57; 0.97, p = 0.027)). In classification models during a depressive state, patients with BD versus patients with UD, there was a sensitivity of 0.70 (SD 0.07), a specificity of 0.77 (SD 0.07), and an AUC of 0.79 (SD 0.03). LIMITATIONS: The relative low symptom severity in the present study may have contributed to the magnitude of the AUC. CONCLUSION: Mobility patterns derived from mobile location data is a promising digital diagnostic marker in discriminating between patients with BD and UD.

Intranasal Ketamine for Depression in Adults: A Systematic Review and Meta-Analysis of Randomized, Double-Blind, Placebo-Controlled Trials.

BACKGROUND: There is growing interest in glutamatergic agents as a treatment for depression, especially intranasal ketamine, which has become a hot topic in recent years. We aim to assess the efficacy and safety of intranasal ketamine in the treatment of major depressive disorder (MDD), especially treatment-resistant depression (TRD). METHODS: We searched Medline, EMBASE, and the Cochrane Library until April 1, 2020 to identify double-blind, randomized controlled trials with allocation concealment evaluating intranasal ketamine in major depressive episodes. Clinical remission, response, and depressive symptoms were extracted by two independent raters. The outcome measures were Montgomery-Asberg Depression Rating Scale (MADRS) score improved from baseline, clinical response and remission, dissociative symptoms, and common adverse events. The analyses employed a random-effects model. RESULTS: Data were synthesized from five randomized controlled trials (RCTs) employing an intranasal esketamine and one RCT employing intranasal ketamine, representing 840 subjects in parallel arms, and 18 subjects in cross-over designs (n = 858 with MDD, n = 792 with TRD). The weighted mean difference of MADRS score was observed to decrease by 6.16 (95% CI 4.44-7.88) in 2-4 h, 9.96 (95% CI 8.97-10.95) in 24 h, and 4.09 (95% CI 2.18-6.00) in 28 day. The pooled relative risk (RR) was 3.55 (95% CI 1.5-8.38, z = 2.89, and p < 0.001) for clinical remission and 3.22 (95% CI 1.85-5.61, z = 4.14, and p < 0.001) for clinical response at 24 h, while the pooled RR was 1.7 (95% CI 1.28-2.24, z = 3.72, and p < 0.001) for clinical remission and 1.48 (95% CI 1.17-1.86, z = 3.28, and p < 0.001) for clinical response at 28 day. Intranasal ketamine was associated with the occurrence of transient dissociative symptoms and common adverse events, but no persistent psychoses or affective switches. CONCLUSION: Our meta-analysis suggests that repeated intranasal ketamine conducted a fast-onset antidepression effect in unipolar depression, while the mild and transient adverse effects were acceptable. SYSTEMATIC REVIEW REGISTRATION: PROSPERO, CRD42020196856.

Transcriptomic profiling as biological markers of depression - A pilot study in unipolar and bipolar women.

OBJECTIVES: A significant challenge in psychiatry is the differential diagnosis of depressive episodes in the course of mood disorders. Gene expression profiling may provide an opportunity for such distinguishment. METHODS: We studied differentially expressed genes in women with a depressive episode in the course of unipolar depression (UD) (n = 24) and bipolar disorder types I (BDI) (n = 13) and II (BDII) (n = 19), and healthy controls (n = 15). RESULTS: Different types of depression varied in the number and type of up or down-regulated genes. The pathway analysis showed: in UD, up-regulated rheumatoid arthritis pathway (including ITGB2, CXCL8, TEK, TLR4 genes), and down-regulated taste transduction pathway (TAS2R10, TAS2R46, TAS2R14, TAS2R43, TAS2R45, TAS2R19, TAS2R13, TAS2R20, GNG13); in BDI, eight down-regulated pathways: glutamatergic synapse, retrograde endocannabinoid signalling, axon guidance, calcium signalling, nicotine addiction, PI3K-Akt signalling, drug metabolism - cytochrome P450, and morphine addiction; in BDII, up-regulated osteoclast differentiation and Notch signalling pathway, and down-regulated type I diabetes mellitus pathway. Distinct expression markers analysis uncovered the unique for UD, up-regulated bladder cancer pathway (HBEGF and CXCL8 genes). CONCLUSIONS: This pilot study suggests a probability of differentiating depression in the course of UD, BDI, and II, based on transcriptomic profiling.

Efficacy, safety and tolerability of formula-based unilateral vs bilateral electroconvulsive therapy in the treatment of major depression: A randomized open label controlled trial.

Electroconvulsive therapy (ECT) remains the most effective treatment of depression, though it is still unclear which of its type is the most beneficial. The aim of this study was to compare the formula-based right unilateral ECT (RUL) with the fronto-temporal bilateral ECT (BT), in terms of their efficacy, safety and tolerability in patients with bipolar or unipolar depression. Ninety-one patients were randomly assigned to either BT (n = 45) or RUL (n = 46) ECT. Brief pulse width (0.5 ms) and a formula-based dosing method were applied. The clinical efficacy was assessed using the Hamilton Depression Rating Scale (HDRS-21).The somatic state was monitored throughout the ECT course and cognitive examination included: general cognitive performance, executive functions, visual-spatial functions, verbal fluency, verbal memory and autobiographical memory. Efficacy outcomes were not found to be significantly different between groups when using higher doses of energy in RUL ECT. Patients in RUL group were less likely to be confused and experienced increased blood pressure. The indices of general cognitive performance and verbal auditory memory were also significantly better this group, while BT ECT did not change these functions. Both ECT types resulted in a decline in the retrieval consistency of autobiographical memory that persists for at least three months and was significantly more marked in BT group as compared to RUL. In conclusion, formula-based RUL ECT does not differ from BT in antidepressant efficacy and has an advantage in terms of safety (lower incidence of increased blood pressure and fewer disturbances of consciousness) and tolerability (impact on cognitive functions).

Structural changes in the hippocampus as a biomarker for cognitive improvements in neuropsychiatric disorders: A systematic review.

Cognitive impairments are a core feature of several neuropsychiatric disorders. A common biomarker for pro-cognitive effects may provide a much-needed tool to select amongst candidate treatments targeting cognition. The hippocampus is a promising biomarker for target-engagement due to the illness-associated morphological hippocampal changes across unipolar disorder (UD), bipolar disorder (BD) and schizophrenia (SCZ). Following the PRISMA guidelines, we searched PubMed and Embase, for clinical trials targeting cognition across neuropsychiatric disorders, with longitudinal structural magnetic resonance imaging (MRI) measures of the hippocampus. Five randomized and three open-label trials were included. Hippocampal volume increases were associated with treatment-related cognitive improvement following treatment with erythropoietin across UD, BD and SCZ, lithium treatment in BD and aerobic exercise in SCZ. Conversely, an exercise intervention in UD showed no effect on hippocampal volume or cognition. Together, these observations point to hippocampal volume change as a putative biomarker-model for cognitive improvement. Future cognition trials are encouraged to include MRI assessments pre- and post-treatment to assess the validity of hippocampal changes as a biomarker for pro-cognitive effects.